Using Customer Service Chatbots To Increase Interactions

As organizations continue to automate their sales and customer service functions to reduce costs without damaging the customer experience, chatbots and other intuitive software programs are gaining ground.

What is a Customer Service Chatbot?

Customer service chatbots interact with the customers on behalf of your business; enabling customers to self-serve online by drawing on NLP (Natural language processing), AI (artificial intelligence), business rules and knowledge bank to answer common questions and requests.

Customers can reach out to your company by sending a message to your customer service chatbot via a messaging platform like Facebook, Skype, Slack etc. Using the business rules that you give it, it will decide whether it can resolve the request or if it should redirect the query to a human agent. The bot will pass on all the relevant information it has collected to the customer service representative.

A chatbot can immediately respond to the questions like:

  • What is the status of my ticket number XP109098?
  • What is your refund policy?
  • Is there any offer on any given product?

Depending on the complexity of the question asked the bots can be trained to a highly efficient scale beyond which the answers could only be given by a human agent.

Why use CUSTOMER SERVICE CHATBOT?

Chatbots make initial customer contact and ongoing maintenance easier for organizations to handle while enhancing the experience for customers at the same time. These days, most customers expect organizations to be available to respond to queries 24/7 – they no longer like to be put on hold or receive an email response for basic information on your product or service. Chatting in real time with your company’s customer service chatbot should be an easy, enjoyable experience for your customers.

In addition to answering the FAQs, chatbots can also be provided with the capability to:

  • Recommend new products
  • Perform simple transactions
  • Conduct customer surveys

Automating a significant amount of your customer service function means you can reduce the number of employees completing manual tasks and focus them on complex tasks that your bot can’t handle. Your employees become an escalation point rather than first contact, increasing your return on investment as labor costs drop. Customer service chatbots can help you streamline your sales and engagement process.

In addition to performing basic transactions, they also collect a significant amount of customer data which you can use to inform your overall business strategy as well as specific functions including customer service and marketing.

How does customer service chatbot work?

You can host customer service chatbot on your website or integrate with popular applications like Facebook Messenger, Skype etc. The latter approach is becoming more and more popular as organizations recognize the potential of bringing their product/service into space where people are spending most of their time, rather than expecting them to seek out to you.

Basic chatbots for customer service are easy to build – they function on rules and respond to specific commands only. They don’t learn any more than you teach them. But, chatbots that use machine learning or Artificial Intelligence (AI) get smarter as they interact with more customers. These complex chatbots are more difficult to create but if you have the right software partner to guide you, it’s worth the investment.

Customer service chatbots and AI

Customer service chatbots when integrated with AI algorithms help us resolve more complex problems like that of Natural language processing. These advanced bots could optimize search operations by filtering out the keywords entered by the user and matching the trait of the products it can compare with.

On a more complex note, the chatbots could give recommendations based on the user reviews of products or any structured or unstructured data available.

To sum up, the more we make the chatbots learn, the more we can reduce the dependence on a human agent and we could achieve this with the help of AI and ML (Machine Learning).

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